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<a href="default__thread__map__volta__tensor__op_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/***************************************************************************************************</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2017-2019, NVIDIA CORPORATION.  All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * Redistribution and use in source and binary forms, with or without modification, are permitted</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> * provided that the following conditions are met:</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> *     * Redistributions of source code must retain the above copyright notice, this list of</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> *       conditions and the following disclaimer.</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> *     * Redistributions in binary form must reproduce the above copyright notice, this list of</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> *       conditions and the following disclaimer in the documentation and/or other materials</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> *       provided with the distribution.</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> *     * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *       to endorse or promote products derived from this software without specific prior written</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> *       permission.</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS &quot;AS IS&quot; AND ANY EXPRESS OR</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE</span></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,</span></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="comment"> * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;</span></div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> * OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,</span></div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> * STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE</span></div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment"> * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="comment"> **************************************************************************************************/</span></div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;<span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="epilogue_2threadblock_2predicated__tile__iterator_8h.html">predicated_tile_iterator.h</a>&quot;</span></div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="include_2cutlass_2gemm_2gemm_8h.html">cutlass/gemm/gemm.h</a>&quot;</span></div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacecutlass.html">cutlass</a> {</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="keyword">namespace </span>epilogue {</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="keyword">namespace </span>threadblock {</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;  <span class="keyword">typename</span> ThreadblockShape,</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;  <span class="keyword">typename</span> WarpShape,</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;  <span class="keywordtype">int</span> PartitionsK,</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;  <span class="keyword">typename</span> ElementOutput,</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;  <span class="keywordtype">int</span> ElementsPerAccess,</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;  <span class="keyword">typename</span> ElementAccumulator</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;&gt;</div><div class="line"><a name="l00052"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp.html">   52</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp.html">DefaultThreadMapVoltaTensorOp</a>;</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;  <span class="keyword">typename</span> ThreadblockShape_,</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;  <span class="keyword">typename</span> WarpShape_,</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;  <span class="keywordtype">int</span> PartitionsK,</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;  <span class="keyword">typename</span> ElementOutput_,</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;  <span class="keywordtype">int</span> ElementsPerAccess</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;&gt;</div><div class="line"><a name="l00064"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__d58c94abc36b7c5c109b55202c6992e7.html">   64</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp.html">DefaultThreadMapVoltaTensorOp</a>&lt;</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;  ThreadblockShape_, </div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;  WarpShape_, </div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;  PartitionsK, </div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;  ElementOutput_, </div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;  ElementsPerAccess, </div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;  <a class="code" href="structcutlass_1_1half__t.html">half_t</a>&gt; {</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;</div><div class="line"><a name="l00072"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__d58c94abc36b7c5c109b55202c6992e7.html#a2d77c871c87f0ccd2a7a0f681f960c95">   72</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__d58c94abc36b7c5c109b55202c6992e7.html#a2d77c871c87f0ccd2a7a0f681f960c95">ThreadblockShape</a> = ThreadblockShape_;</div><div class="line"><a name="l00073"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__d58c94abc36b7c5c109b55202c6992e7.html#a9d08a84426bb7ad1891b21e62ba218a1">   73</a></span>&#160;  <span class="keyword">using</span> WarpShape = WarpShape_;</div><div class="line"><a name="l00074"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__d58c94abc36b7c5c109b55202c6992e7.html#af5f1c910c0ade6b79dbbe110e9ac2b96">   74</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kPartitionsK = PartitionsK;</div><div class="line"><a name="l00075"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__d58c94abc36b7c5c109b55202c6992e7.html#a41a293586131c32370d97402dfb5b7cf">   75</a></span>&#160;  <span class="keyword">using</span> ElementOutput = ElementOutput_;</div><div class="line"><a name="l00076"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__d58c94abc36b7c5c109b55202c6992e7.html#a1594f8bd01920460fe88e3a568b9ef3a">   76</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kElementsPerAccess = ElementsPerAccess;</div><div class="line"><a name="l00077"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__d58c94abc36b7c5c109b55202c6992e7.html#a1e158d68790c48b49fad385153dfdb55">   77</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1half__t.html">ElementAccumulator</a> = <a class="code" href="structcutlass_1_1half__t.html">half_t</a>;</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;  <span class="comment">// Definitions</span></div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;</div><div class="line"><a name="l00083"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__4433cc988100e98097a748d2670fb0fc.html">   83</a></span>&#160;  <span class="keyword">struct </span>Detail {</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;</div><div class="line"><a name="l00085"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__4433cc988100e98097a748d2670fb0fc.html#abefdea13828326ce59cf4768483e3a96">   85</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kTensorOpRows = 16;</div><div class="line"><a name="l00086"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__4433cc988100e98097a748d2670fb0fc.html#a698b74b827c49a4cbc341fccd15f22eb">   86</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kWarpSize = 32;</div><div class="line"><a name="l00087"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__4433cc988100e98097a748d2670fb0fc.html#a2f6ac9f5289c96c724bbf22598c5bb48">   87</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kInterleavedTilesM = WarpShape::kM / 32;</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;      !(ThreadblockShape::kM % WarpShape::kM) &amp;&amp;</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;      !(ThreadblockShape::kM % WarpShape::kM), <span class="stringliteral">&quot;Divisibility&quot;</span>);</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;    <span class="keyword">using</span> <a class="code" href="structcutlass_1_1gemm_1_1GemmShape.html">WarpCount</a> = <a class="code" href="structcutlass_1_1gemm_1_1GemmShape.html">gemm::GemmShape</a>&lt;</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;      ThreadblockShape::kM / WarpShape::kM,</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;      ThreadblockShape::kN / WarpShape::kN,</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;      kPartitionsK</div><div class="line"><a name="l00098"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__4433cc988100e98097a748d2670fb0fc.html#ad7b0c335acfd70439d9e4190ca66038e">   98</a></span>&#160;    &gt;;</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;</div><div class="line"><a name="l00101"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__4433cc988100e98097a748d2670fb0fc.html#a00cbee272e5c9b0e4e11065054f60fa0">  101</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kThreads = WarpCount::kCount * kWarpSize;</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;    <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape.html">Shape</a> = <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape.html">cutlass::epilogue::threadblock::OutputTileShape</a>&lt;</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;      ThreadblockShape::kN,   <span class="comment">// column</span></div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;      4,                      <span class="comment">// row</span></div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;      4,                      <span class="comment">// group</span></div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;      WarpCount::kM,          <span class="comment">// cluster</span></div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;      1                       <span class="comment">// tile</span></div><div class="line"><a name="l00109"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__4433cc988100e98097a748d2670fb0fc.html#aca4db467faaec18b0fc18e697b4f946c">  109</a></span>&#160;    &gt;;</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;    </div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;    <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape.html">Count</a> = <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape.html">cutlass::epilogue::threadblock::OutputTileShape</a>&lt;</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;      1,                                <span class="comment">// column</span></div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;      2,                                <span class="comment">// row</span></div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;      kInterleavedTilesM,               <span class="comment">// group</span></div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;      1,                                <span class="comment">// cluster</span></div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;      WarpShape::kM / kTensorOpRows     <span class="comment">// iterations</span></div><div class="line"><a name="l00118"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__4433cc988100e98097a748d2670fb0fc.html#a037e7c6716020fa2297eee14ba9704b0">  118</a></span>&#160;    &gt;;</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;  };</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;  <span class="comment">// ThreadMap</span></div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;  </div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileOptimalThreadMap.html">Type</a> = <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileOptimalThreadMap.html">OutputTileOptimalThreadMap</a> &lt;</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;    <span class="keyword">typename</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape.html">Detail::Shape</a>,</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    <span class="keyword">typename</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape.html">Detail::Count</a>,</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;    Detail::kThreads,</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;    kElementsPerAccess,</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    <a class="code" href="structcutlass_1_1sizeof__bits.html">sizeof_bits&lt;ElementOutput&gt;::value</a></div><div class="line"><a name="l00132"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__d58c94abc36b7c5c109b55202c6992e7.html#a5eabbd828df92738af9fcfc243936b42">  132</a></span>&#160;  &gt;;</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;};</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;<span class="keyword">template</span> &lt;</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;  <span class="keyword">typename</span> ThreadblockShape_,</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;  <span class="keyword">typename</span> WarpShape_,</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;  <span class="keywordtype">int</span> PartitionsK,</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;  <span class="keyword">typename</span> ElementOutput_,</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;  <span class="keywordtype">int</span> ElementsPerAccess</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;&gt;</div><div class="line"><a name="l00145"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__95db04b7b72e34283958bd7fbf851d16.html">  145</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp.html">DefaultThreadMapVoltaTensorOp</a>&lt;</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;  ThreadblockShape_,</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;  WarpShape_,</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;  PartitionsK,</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;  ElementOutput_,</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;  ElementsPerAccess,</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;  float&gt; {</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;</div><div class="line"><a name="l00153"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__95db04b7b72e34283958bd7fbf851d16.html#a553ef47868ffab39e8b56e4732f0adc2">  153</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__95db04b7b72e34283958bd7fbf851d16.html#a553ef47868ffab39e8b56e4732f0adc2">ThreadblockShape</a> = ThreadblockShape_;</div><div class="line"><a name="l00154"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__95db04b7b72e34283958bd7fbf851d16.html#ab48d0b40b527742a1021348c8c2110c4">  154</a></span>&#160;  <span class="keyword">using</span> WarpShape = WarpShape_;</div><div class="line"><a name="l00155"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__95db04b7b72e34283958bd7fbf851d16.html#a8cbd8dd46c0afabd3d15756e3feba876">  155</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kPartitionsK = PartitionsK;</div><div class="line"><a name="l00156"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__95db04b7b72e34283958bd7fbf851d16.html#a283940e6c5b2b9b73c17aa83b9d73be9">  156</a></span>&#160;  <span class="keyword">using</span> ElementOutput = ElementOutput_;</div><div class="line"><a name="l00157"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__95db04b7b72e34283958bd7fbf851d16.html#a370bb2559e8d10b20a5a424359efc1fb">  157</a></span>&#160;  <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kElementsPerAccess = ElementsPerAccess;</div><div class="line"><a name="l00158"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__95db04b7b72e34283958bd7fbf851d16.html#aaafecab7ef7d86ac178d2302c91a902a">  158</a></span>&#160;  <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__95db04b7b72e34283958bd7fbf851d16.html#aaafecab7ef7d86ac178d2302c91a902a">ElementAccumulator</a> = float;</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;  <span class="comment">// Definitions</span></div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;  <span class="comment">//</span></div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;</div><div class="line"><a name="l00164"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__52116c60c62f0fd520071558e42b814f.html">  164</a></span>&#160;  <span class="keyword">struct </span>Detail {</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;</div><div class="line"><a name="l00166"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__52116c60c62f0fd520071558e42b814f.html#aa9e5d51def1064ea8087ffddfafdfb26">  166</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kTensorOpRows = 16;</div><div class="line"><a name="l00167"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__52116c60c62f0fd520071558e42b814f.html#afb104fd1885be18e82c1b27ff144a861">  167</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kWarpSize = 32;</div><div class="line"><a name="l00168"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__52116c60c62f0fd520071558e42b814f.html#a995d3fd248d01a16c449046aaf4fd00a">  168</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kInterleavedTilesM = WarpShape::kM / 32;</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;    <a class="code" href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a>(</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;      !(ThreadblockShape::kM % WarpShape::kM) &amp;&amp;</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;      !(ThreadblockShape::kM % WarpShape::kM), <span class="stringliteral">&quot;Divisibility&quot;</span>);</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;    <span class="keyword">using</span> <a class="code" href="structcutlass_1_1gemm_1_1GemmShape.html">WarpCount</a> = <a class="code" href="structcutlass_1_1gemm_1_1GemmShape.html">gemm::GemmShape</a>&lt;</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;      ThreadblockShape::kM / WarpShape::kM,</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;      ThreadblockShape::kN / WarpShape::kN,</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;      kPartitionsK</div><div class="line"><a name="l00179"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__52116c60c62f0fd520071558e42b814f.html#a76585052bb136aff1ada04e446109345">  179</a></span>&#160;    &gt;;</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;</div><div class="line"><a name="l00182"></a><span class="lineno"><a class="line" href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__52116c60c62f0fd520071558e42b814f.html#a8a9e67935629344f7e700701101c2223">  182</a></span>&#160;    <span class="keyword">static</span> <span class="keywordtype">int</span> <span class="keyword">const</span> kThreads = WarpCount::kCount * kWarpSize;</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;    <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape.html">Shape</a> = <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape.html">cutlass::epilogue::threadblock::OutputTileShape</a>&lt;</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160; 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   </div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;    <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape.html">Count</a> = <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape.html">cutlass::epilogue::threadblock::OutputTileShape</a>&lt;</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;      1,                                <span class="comment">// column</span></div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;      2,                                <span class="comment">// row</span></div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;      kInterleavedTilesM,               <span class="comment">// group</span></div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;      1,                                <span class="comment">// cluster</span></div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160; 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 <span class="keyword">using</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileOptimalThreadMap.html">Type</a> = <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileOptimalThreadMap.html">OutputTileOptimalThreadMap</a> &lt;</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;    <span class="keyword">typename</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape.html">Detail::Shape</a>,</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;    <span class="keyword">typename</span> <a class="code" href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape.html">Detail::Count</a>,</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;    Detail::kThreads,</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;    kElementsPerAccess,</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160; 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ThreadblockShape_, WarpShape_, PartitionsK, ElementOutput_, ElementsPerAccess, float &gt;::ElementAccumulator</a></div><div class="ttdeci">float ElementAccumulator</div><div class="ttdef"><b>Definition:</b> default_thread_map_volta_tensor_op.h:158</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileOptimalThreadMap_html"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileOptimalThreadMap.html">cutlass::epilogue::threadblock::OutputTileOptimalThreadMap</a></div><div class="ttdef"><b>Definition:</b> output_tile_thread_map.h:228</div></div>
<div class="ttc" id="namespacecutlass_html"><div class="ttname"><a href="namespacecutlass.html">cutlass</a></div><div class="ttdef"><b>Definition:</b> aligned_buffer.h:35</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape_html"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1OutputTileShape.html">cutlass::epilogue::threadblock::OutputTileShape</a></div><div class="ttdoc">Tuple defining point in output tile. </div><div class="ttdef"><b>Definition:</b> output_tile_thread_map.h:57</div></div>
<div class="ttc" id="epilogue_2threadblock_2predicated__tile__iterator_8h_html"><div class="ttname"><a href="epilogue_2threadblock_2predicated__tile__iterator_8h.html">predicated_tile_iterator.h</a></div><div class="ttdoc">Epilogue for threadblock scoped GEMMs using Tensor Ops. </div></div>
<div class="ttc" id="structcutlass_1_1half__t_html"><div class="ttname"><a href="structcutlass_1_1half__t.html">cutlass::half_t</a></div><div class="ttdoc">IEEE half-precision floating-point type. </div><div class="ttdef"><b>Definition:</b> half.h:126</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__d58c94abc36b7c5c109b55202c6992e7_html_a2d77c871c87f0ccd2a7a0f681f960c95"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__d58c94abc36b7c5c109b55202c6992e7.html#a2d77c871c87f0ccd2a7a0f681f960c95">cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp&lt; ThreadblockShape_, WarpShape_, PartitionsK, ElementOutput_, ElementsPerAccess, half_t &gt;::ThreadblockShape</a></div><div class="ttdeci">ThreadblockShape_ ThreadblockShape</div><div class="ttdef"><b>Definition:</b> default_thread_map_volta_tensor_op.h:72</div></div>
<div class="ttc" id="include_2cutlass_2gemm_2gemm_8h_html"><div class="ttname"><a href="include_2cutlass_2gemm_2gemm_8h.html">gemm.h</a></div><div class="ttdoc">Defines common types used for all GEMM-like operators. </div></div>
<div class="ttc" id="structcutlass_1_1sizeof__bits_html"><div class="ttname"><a href="structcutlass_1_1sizeof__bits.html">cutlass::sizeof_bits</a></div><div class="ttdoc">Defines the size of an element in bits. </div><div class="ttdef"><b>Definition:</b> numeric_types.h:42</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__95db04b7b72e34283958bd7fbf851d16_html_a553ef47868ffab39e8b56e4732f0adc2"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_3_01ThreadblockShape__95db04b7b72e34283958bd7fbf851d16.html#a553ef47868ffab39e8b56e4732f0adc2">cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp&lt; ThreadblockShape_, WarpShape_, PartitionsK, ElementOutput_, ElementsPerAccess, float &gt;::ThreadblockShape</a></div><div class="ttdeci">ThreadblockShape_ ThreadblockShape</div><div class="ttdef"><b>Definition:</b> default_thread_map_volta_tensor_op.h:153</div></div>
<div class="ttc" id="structcutlass_1_1gemm_1_1GemmShape_html"><div class="ttname"><a href="structcutlass_1_1gemm_1_1GemmShape.html">cutlass::gemm::GemmShape</a></div><div class="ttdoc">Shape of a matrix multiply-add operation. </div><div class="ttdef"><b>Definition:</b> include/cutlass/gemm/gemm.h:57</div></div>
<div class="ttc" id="platform_8h_html_adde4c9ea91b753491851361a4198c009"><div class="ttname"><a href="platform_8h.html#adde4c9ea91b753491851361a4198c009">static_assert</a></div><div class="ttdeci">#define static_assert(__e, __m)</div><div class="ttdef"><b>Definition:</b> platform.h:153</div></div>
<div class="ttc" id="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp_html"><div class="ttname"><a href="structcutlass_1_1epilogue_1_1threadblock_1_1DefaultThreadMapVoltaTensorOp.html">cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp</a></div><div class="ttdoc">Defines the optimal thread map for TensorOp accumulator layouts. </div><div class="ttdef"><b>Definition:</b> default_thread_map_volta_tensor_op.h:52</div></div>
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